In Stochastic Environments
As I understand it I have the honor, of which I am most definetly not worthy, of being the first Gomulkiewicz Keynote Speaker. Many of you here knew him but for those prospective students who didn’t that good fortune to meet him, he was a PI here at WSU but sadly passed away in 2023. He was a theoretical population geneticist and had a reputation for being tough. More than one of my fellow grad students warned me away from chosing him to be on my commitee during me first year. I am so grateful that I chose not to listen to that advice.
“The fitness of a lineage in a fluctuating environment is the time average of its fitness over the sequence of static conditions it encounters.”1
https://medium.com/data-science-at-microsoft/how-large-language-models-work-91c362f5b78f
Can we reconstruct historical of range expansion routes?
Westward range expansion from middle latitudes explains the Mississippi River discontinuity in a forest herb of eastern North America2
Sweeps in space: leveraging geographic data to identify beneficial alleles in Anopheles gambiae3
Predicting the fine-scale spatial distribution of zoonotic reservoirs using computer vision4
Predicting the fine-scale spatial distribution of zoonotic reservoirs using computer vision4
Predicting the fine-scale spatial distribution of zoonotic reservoirs using computer vision4
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Quantifying Underreporting in Wildlife Disease Surveillance
2008-2019 - 131 countries - 56 diseases - 100,450 articles
Quantifying Underreporting in Wildlife Disease Surveillance
Yes
Almost all of my academic friends, have all worked in both academic and non-academic environments at some point
I know post-graduates who are
More importantly, an generative AI is a based on massively complicated statistical engines designed to answer the question, “what should I say next?”
Focus on transferrable skills like communication, technical writing, data viz, coding, problem solving.
• The best thing about SBS (and probably grad school anywhere) is the people. Make a point of meeting them, talking to them, asking for their help, and offering yours when you can. That will also have the side-effect of making you one of those great people folks meet in grad school.
• From the day you come in to the day you leave, remember that you’re here to learn. Try stuff, fail, ask for help, change directions. Being bad at something is good. That’s just something you can try to improve at, which is why you’re here.
Self-Evaluated Workload: Prioritize balance and adjust work hours based on personal assessment, not peer pressure or toxic “overwork” culture.
Critical Analysis: Always question why specific methods or techniques are used in research; avoid adopting approaches solely because they’re precedent—understand their rationale.
Workflow Investment: Develop and maintain efficient workflows tailored to your needs, even if it requires upfront time.
Advisor Relationship: Choose an advisor you can collaborate with effectively, as their mentorship profoundly impacts your PhD experience. Proactively nurture this relationship to navigate challenges.
Doing science beyond grad school involves
Useful tools